Update 11 November 2023: I’ve talked with a lot of people, both interviews for the podcast and informational chats, over the past few weeks and have made some interesting discoveries. So, in addition to helping us all understand AI and how to use it in our work, I’m adding to this podcast’s scope coverage of people working in content roles on AI products. Like any other software, AI products need content strategy, content design, UX writing, technical documentation, etc., and we’ll hear from those folks soon.
Here’s the video version of this episode:
Welcome to the Content and AI podcast. This is episode number 0, an introduction to the show. This episode is just me talking about my intention and plans. Going forward, it will be conversations with experts on both AI and content practice.
My intent with this new podcast is twofold: one, to demystify the family of technologies and practices known as artificial intelligence and, two, to democratize the use of AI across the span of content use cases, everything from research and discovery, to content creation and authoring, to content design, content engineering, and content operations. All the stuff we do.
I’ll talk to folks in the AI field of course – and at first that will largely be a bunch of old white guys, which in itself points to some of data sampling and bias problems that AI practitioners face.
But I’ll also talk to a diverse range of content practitioners working in product content, support documentation, conversational design, website content, marketing content, content-marketing content – anyone who’s adding AI to their digital content workflows – which is pretty much all of us at this point.
We’ve already seen the applications of AI all over the place:
- auto correct and auto fill in forms
- digital assistants like Alexa, Cortona, Bixby, and Siri
- search engines
- social media feeds
- personalized content in advertising and on websites and digitial products
- recommendations from ecommerce merchants
- robots on assembly lines
- fraud prevention
- drug discovery
- medical diagnosis
- generative AI, the computer-generated text, and image, and videos that are flooding your in box and social media feeds
We’ll go under the hood (or as they say in England, the bonnet, I’m recording this in London) – we’ll go under the hood, behind the scenes top look at the scope of AI. Not all agree on the precise scope – but we’ll look at topics like:
- NLP, natural language processing, and its applications in areas like conversation design
- machine learning – statistical modeling of data – embeddings and vectorization and predicting which words come next
- knowledge representation – bringing real-world facts to the table, which we’re already seeing with practices like retrieval augmented generation (RAG)
- neural networks – machine-based augmented decision making
- expert systems – rules-based ways to augment human decision making since the 70s
- computer vision
- AI ethics and Silicon Valley hype
To that last point, we’ll pay attention to folks like Timnit Gebru and her collaborator Emily M. Bender. Timnit Gebru is the AI researcher who was fired from Google for pointing out the shortcomings in their approach. She and Bender coauthored the now-famous “stochastic parrots” academic paper. And one of my early guests, one of those old white guys, a delightful and remarkably accomplished human named Paco Nathan – will help us see the current state of AI through lens of an industry veteran with deep deep deep experience in the technical foundations of AI and a ton of experience in the tech startup world. So we’ll try to balance the tech hype coming out of Silicon Valley. But we can’t and won’t ignore that hype – regardless of its merits, they’ve got the attention of executives and decision makers and the media, so we’ll definitely keep an eye on the the big players in the AI space like OpenAI, Anthropic, and Google’s Deepmind, and show you how to best use their products.
Finally, we’ll keep on the radar screen the concept of art general intelligence (AGI).
But my main intent is to democratize AI technology to help content practitioners understand and use AI as expertly and efficiently as possible (edit: and to help content practitioners working on AI products).
We’ve already seen many ways that AI can help content folks:
- content creation – relieving the terror of the blank page, tedious outline tasks, research, etc
- authoring, enterprise UX, auto- and assisted tagging, voice, tone, and style governance, creating content variants, repurposing existing content, etc.
- strategy formulation
- content design
- content engineering
- content operations
AI’s going to be able to help us across the span of content practice. No matter what kind of content work you do, you’ll soon be using AI in any number of ways (edit: and you’ll likely be helping to design the next generation of AI tools).
Anyhow, welcome to the Content and AI podcast. I and my guests are here to help you navigate this dynamic new landscape and to use AI effectively in your content work.
If you’re doing interesting work with AI – and your boss will let you talk about it – DM me on LinkedIn – I’m always happy to chat about how we might get you on the show, or just chat about AI.